Institutionalizing world-class quality engineering practices is key to protecting business and delivering a world-class customer experience with first-time-right quality at speed. Our differentiated capabilities in testing allow us to meet our customers’ current and future needs for next-generation testing services.
We provide the following Smart Testing Solutions to cater to our customer’s needs.
Businesses are migrating to a conversational assistant that enables interaction with their customers, helps them with queries to close business processes quicker. Conversational bots are on high demand. With increasing trends, the number of chatbots implemented across is also rising. The need for robust testing of these bots becomes vital to ensure that the customer experience is higher when the bots are deployed in production.
The risk of end users not returning to the bot or pages due to unpleasant experiences can lead to loss of business as well. Hexaware offers a multi-dimensional approach to test Chatbots / Voicebots (AI-based or Rule-based), both web / mobile hosted on entity fulfilment, humanness index, conversational flow, emotional quotient, context intelligence, etc. This solution built-on a combination of open-source frameworks and custom libraries helps achieve 30% test design automation for Chatbots and 80% test execution automation. Due to the exhaustive nature of testing that can be done on AI bots, the automated approach brings down the test cycle time and ensures higher coverage.
Our solution caters to testing across major Chatbot Development Platforms, Services and NLP engines such as Google DialogFlow, Amazon Lex, Microsoft Luis, Microsoft bot framework, IBM Watson, Rasa NLU, Google Home, Alexa Skills, etc.
Predictive Test Analytics
Predictive Test Analytics Platform (PTAP) is a web platform embedded with Machine Learning to facilitate predicting future release patterns based on historical information of previous releases’ data across the entire SDLC of any project / program.
This solution consumes any relevant data from test management tools, defect tracking tools, application production logs, etc. to understand a past pattern and predict the outcome of the future or current releases. Predictions such as optimal velocity for a scrum team, probable estimation in efforts for a release, chances of whether a release will result in schedule variance, probable defect leakage in a release or frequency of repeated similar production incidents can help mitigate risk earlier.
Leveraging PTAP gives the management an in-depth view of what would be the future of the upcoming releases.
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